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Relationship between Performance Appraisal Politics,
Organizational Commitment and Turnover Intention.
Dr; Aziz Javed,
Dep’t of Business Administration; Gomal University D.I.Khan .KPK Pakistan.
Email; Azizjaved_mba@yahoo.com
Naveed Saif; (Corresponding Author)
Dep’t of Business Administration;
Gomal University D.I.Khan .KPK Pakistan
Email; Naveedsaif_naveedsaif@yahoo.com
Muhammad Imran Qureshi;
Department of Commerce;
Gomal University D.I.Khan .KPK Pakistan
Khalid Rehman;
Lecturer; Dep’t of Business Administration;
Gomal University D.I.Khan .KPK Pakistan.
Farhat ullah Khan;
Lecturer ;Dep’t of Business Administration;
Gomal University D.I.Khan .KPK Pakistan.
Muhamamd Saqib Khan;
Lecturer; Dep’t of Business Administration;
Gomal University D.I.Khan .KPK Pakistan.
Abstract:
Most of the studies define organizational commitment as commitment specifically
targeted towards the organization as an administrative entity. Organizational commitment has been found both as
an antecedent and consequence of number of work related variables. Numerous research articles show that
organizational commitment is the consequence of personal variables, work environment variable and as predictor
of absenteeism, performance and turnover. Going through the literature on organizational commitment
consequences, scholar strongly believes that the strongest and most predictable behavioral outcome of the
employee commitment is reduced turnover. The focus of this research was to study and examine the effects of
performance appraisal politics . organizational commitment and turnover intentions. The population for this
research was defined as pharmaceutical marketing firms (private sector) of Pakistan, including national and
multinational firms. Data was collected from 10 pharmaceutical firms (both national and multinational). A
total of 300 questionnaires were distributed and out of those, 270 complete questionnaires were gathered, hence
depicting a response rate of 90 %. This study examined the effects of performance appraisal politics on
organizational commitment, and turnover intention. Initially the perceptions of appraisal politics was viewed as
single general variable, but after factor analysis of the items used to assess the variables, resulted in two
independent factors.i.e one linked to political motives that benefit employees and other is linked to personal bias
and punishment motive.
KEY WORDS; Organizational commitment, Turnover intentions, Performance appraisal politics
Introduction:
Most of the studies define organizational commitment as commitment specifically
targeted towards the organization as an administrative entity. Organizational commitment has been found both as an
antecedent and consequence of number of work related variables. Numerous research articles show that
organizational commitment is the consequence of personal variables, work environment variable and as predictor
of absenteeism, performance and turnover. One of the performance criteria among the organizations is to retain
employees and minimize turnover. Besides significant research progress, it is still confusion among

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organizational researchers to know what causes employees to stay with or leave their organization. Some of
the factors causing turnover are, institutional factors (physical working conditions, pay, job skills, organizational
structure, and management style etc), external factors (the labor market), employee personal characteristics
(intelligence, personal history, sex, age, interests, and experience), and employee’s reaction to his/her job (job
satisfaction,
job involvement and job expectation). When employees and organization are effectively integrated, the
relation between the two is long lasting. Such relation of integration has strong bearing on absenteeism, turnover and
commitment (Zeffane, 1994. cited in Tosi and Slocum, 1984)
In this research, the scholar is working on, effects of performance appraisal politics on
job satisfaction, organizational commitment and turnover intentions in Pakistan and especially n private sector. Also
that the job satisfaction mediate the relation between performance appraisal politics and turnover intentions.
Almost similar research was conducted by M.L.Poon in Malaysia, published in 2003. The researcher has
extended the study by adding organizational commitment to the model and also, it was conducted in
pharmaceutical marketing sector (private sector) organizations in Pakistan.
Literature Review:
Considering the literature on organizational commitment, it is apparent that little
consensus exists among organizational researchers with respect to the meaning of the term. As the area
developed, researchers from various disciplines ascribed different meaning to organizational commitment.
However, some generally accepted definitions are, according to Mowday et al, “An attitude or an orientation
toward the organization which links or attaches the identity of the person to the organization” and “A set of
being in which an individual becomes bound by his actions and through these actions to beliefs that sustain the
activities and his own involvement”. Etzioni, (1961), noted that commitment can have following three forms.
Calculative commitment,
Moral commitment is defined as when an employee shows a positive and intense orientation towards
organizational goals, values and norms of the organization. An employee is very much involved in organization as
he feels the organization is pursuing useful social goals. Calculative commitment represents, less intense
relationship with the organization and is mostly based on exchange theory. Employee perceive that they are getting as
much rewards from the organization as much they contribute services to it. Employees actually perceive that there
is a balance between what he is doing for organization and what organization is doing in reward for him.
Alienative commitment involves, negative orientation towards the organization. Organizational
commitment is outcome of many factors like personal
characteristics, job or role-related characteristics and work experience. It has also some consequences (for
organization and employee himself) like job performance, tenure with the organization, tardiness and turnover.
Table 2.4 on page 37 (Mowday et al). Allen and meyer, 1996, noted the three different types of commitment as
affective, continuance and normative commitment. Affective commitment refers to involve in and emotional
attachment to the organization. Continuance commitment refers to the employee’s recognition of the costs
associated with leaving the organization while normative commitment refers to the commitment based on
the sense of obligation to the organization.
Research has shown that loyalty level between employees and organizations have been decreased, due to high
job mobility among young workers and high rate of merge and acquisitions in the market. This has lead to
change the concept of organization in the mind of employee as organizational boundaries have become less
concrete and more virtual. Human resource management practices generate positive employee attitudes, which lead
to improved performance. This shows the importance of employee’s attitude. Organizational commitment and job
satisfaction are the attitudes that are affected by the human resource management practices (Meyer, 1997; Edger
and Geare, 2005, Rayton, 2006).
H1: Performance appraisal politics and organizational commitment are negatively related:
Vigoda, 2007, noted that lack of fairness in the organizational processes(i.e.

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performance appraisal), is the major cause of higher perceptions of organizational politics and therefore affects
organizational performance and employees’ attitude towards work and organization. Higher the perception of
organizational politics, lower is the employee’s job satisfaction and organizational commitment. Perception of
organizational politics directly and indirectly affects the employees work attitudes (job satisfaction, organizational
commitment etc).
H2: Organizational commitment and turnover intentions are negatively related:
Going through the literature on organizational commitment consequences, scholar
strongly believes that the strongest and most predictable behavioral outcome of the employee commitment is
reduced turnover. Highly committed employees are willing to work in organization and working for the
achievement of organizational goals and objectives and hence less likely to quit. Many research studies have
been conducted on the relationship between organizational commitment and turnover intentions, majority of
which have shown highly significant and inverse relationship between the two. Work environment, besides other
factors, is the major antecedent of organizational commitment. Mentioned that there is significant inverse
relationship between organizational commitment and turnover intentions (Mowday et al pp.23-27). Brunetto and
Far-wharton, 2003, research suggests a positive relationship between organizational commitment and job
satisfaction and negative relationship between organizational commitment and intentions to quit. Emmert and
Taher
(1992), noted that employees’ job satisfaction and organizational commitment were found high in those
organizations where there is a positive feedback environment both vertically between supervisors and employees’
and horizontally among workers.
Methodology
Method:
The focus of this research was to study and examine the effects of performance
appraisal politics on job satisfaction, organizational commitment and turnover intentions. The population for this
research was defined as pharmaceutical marketing firms (private sector) of Pakistan, including national and
multinational firms. Data was collected from 10 pharmaceutical firms (both national and multinational). A
total of 300 questionnaires were distributed and out of those, 270 complete questionnaires were gathered, hence
depicting a response rate of 90 %.
Keeping in view the time and cost limitation, quota sampling technique was used where by the questionnaires
were distributed to specified sub-groups and respondents were selected non-randomly. All the respondents chosen
were marketing job holders and adequate educational back ground and experience to comprehend the
questionnaire except the few which needed some detail and clarification. The following table shows the
name of the organization, type, No: of questionnaires distributed, No: of questionnaires received and response
rate of the particular organization.
Procedure
The design of this research was cross sectional hence data was collected at one point of time. The researcher
approached the marketing personnel individually and sometimes in a group with their managers. After seeing
the interest of manager and individuals, and getting ermission for administering the questionnaire, (Appendix
F), were distributed to the employees. The questionnaires were distributed manually by the researcher himself.
Similarly the questionnaires were gathered by the researcher without involving the HR department. This was done in
order to maintain the complete anonymity of responses.

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Key Variables
Following variables were identified in my study:
a) Independent variable:
1) Performance Appraisal Politics (PAP)
B) Dependent variables:
1) Organizational Commitment
2) Turn over Intention
Measures
The measures used were perceptions of performance appraisal politics, organizational commitment, job
satisfaction and turnover intentions. Respondents were asked to answer all items of the questionnaire for these
measures using a rating scale ranging from 1 (strongly disagree) to 7 (strongly agree). For each measure, the
ratings on items were averaged to farm an overall score for the measure. Higher score indicated higher standing on
the measure.
Perceptions of Performance Appraisal Politics: The instrument of political considerations in performance
appraisal (QPCPA; Tziner et al., 1996) was the source from which items were selected to use for predictable
variable. Eight items questionnaire was used for this part to assess respondents’ perceptions of political
manipulation behind the inflation or deflation of employees’ performance ratings in performance appraisal
process conducted in their organizations. Sample items are, “Managers in my organization avoid ratings that
have negative consequences for employees” and “Managers in my organization avoid low ratings to avoid written
record of poor performance”.
Organizational commitment: Six items from 9-item abbreviated version of Mowday, Steers, and Porter’s (1979) scale
was used to measure organizational commitment. Sample items in the scale include; “I enjoy discussing my
organization with people outside it” and “The organization has a great deal of personal meaning for me”. The
response scale has been seven point Likert-type scale ranging from one (strongly disagree) to seven (strongly agree).
Turnover intentions: A turnover intention was measured with five-item dependable continuance scale
developed by Tsui, Pearce, Porter, and Tripoli’s (1997) and by Bozeman and Perrewe, 2001; Vigoda, 2000. This
five item scale corresponds to the intent-to-stay idea in the organizational behavior literature. The higher values in
the scale correspond to leaving the organization and lower values correspond to intent-to-stay. Sample items in
the scale include;” I will probably look for a new job in the next year” and “I often think about quitting my present
job” The response scale has been seven point Likert-type scale ranging from one (strongly disagree) to seven
(strongly agree).
DATA ANALYSIS PROCEDURES
The following statistical techniques were applied in testing the hypothesis using the Statistical Package for the
Social Sciences (SPSS Version 15). Before commencement of the analysis the data for all 25 items and 270 cases
was analyzed for missing values.
PAP
OC
TOI

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Data Cleaning
Univariate outliers were detected through inspection of Z scores, histograms, box plots
and normal probability plots. The data was analyzed for checking the assumptions of normality, linearity
and multicollinearity. Normality of data was assessed through the inspection of values of sknewness and
kurtosis as well through graphical inspection of histograms and normal probability plots. Linearity was
assessed by drawing the scatter biplots.
Reliability of scales
Reliability is the extent to which an item, scale, or instrument will produce the same values when given in
different times, places, or populations (Nunnally and Bernstein 1994). It is a measure of repeatability or replication.
Internal consistency reliability is the degree to which individual scale items correlate with one another or with
the entire scale (Nunnally and Bernstein 1994). A scale in internally consistent if each item in a scale measures
the same concept (Kline 2005, p.59). The most widely used index of internal consistency reliability is Cronbach's
(1951) alpha or coefficient alpha. A calculation of Cronbach's alpha was used to assess the reliability of the each of
the
four constructs identified in the exploratory factor analysis. The conventional standard is that Cronbach's alpha
should be .70 or higher for a scale to be considered reliable (Nunnally and Bernstein 1994).
Validity of scales
Validity of measurement includes construct validity. Construct validity includes
structural, convergent, and discriminant validity. Convergent validity indicates “the degree to which two measures
of the same concept is correlated” (Hair et al., 1998). Discriminant validity assesses “the degree to which two
conceptually similar concepts are distinct” (Hair et al., 1998).
Convergent and discriminant validity of 4 scales(i.e. performance appraisal politics, organizational
commitment, and turnover intentions) were analyzed by method provided by Fornell and Larcker (1984) and
Anderson and Gerbing (1988). These methods urge to use average variance extracted for each factor/scale and
to observe the significance of each item loadings.
ANALYSIS & RESULTS
Preparation of data
Missing Value Analysis
For the given data set, there were in total 20 missing cases. 12 cases had more than
50% of the missing values on all variables. As these were the cases identified more severe, so there elimination
deemed necessary by applying the criteria of more than 50% missing identified by (Hair et al. 2006). In rest of
the data (258) I had, 4 cases with 10 missing values, and 4 cases with 5 missing values,. In order to deal with
missing values, it is deemed necessary to find out whether the data is scattered over variables and cases in the
random or nonrandom manner. Second, once the randomness or non randomness of data is established then
imputation technique would be applied in order to replace these missing values. To determine whether the missing
data are distributed randomly across the cases and the variables. A method outlined by Hair et al. (2006), was
followed to find out the randomness of the missing data. In this method dichotomous variables were formed by
replacing valid values with a value of one and missing data with value of zero. The resulting correlations
between the dichotomous variables indicated the extent to which missing data were related in pairs of variables.
Correlations among the all dichotonomous variables were analyzed. Since large number of the variables were
having zero number of missing values so most of the correlations could not be calculated. However, for the other
variables with the missing values, the values of correlations were all below the level of 0.28, indicating that there does
not exist any systematic pattern between the valid values and missing values further decreased the chances of
eliminating any variable due to non random pattern.
As missing data were random, I resorted to data imputation. Although we had many
alternatives to deal with missing values, like mean substitution, hot deck, regression methods, expectation
maximization, raw maximum likelihood and multiple imputation (Schafer and John, 2002), for simplicity reason
and as data was missing completely at random I resorted to Mean substitution. After this imputation, I had a total
of 258 cases.
Univariate Detection of Outliers.
Outliers are cases with such extreme values on one variable or a combination of
variables that they distort statistics (Tabachinick, 1996). Outliers can be found in both univariate and
multivariate situations. Since they lead to both Type I and Type II errors, so there detection is deemed necessary
for any analysis. For our data we will follow the methods identified by Tabachnikc for detecting and dealing with

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the outliers. I adopted two methods for detection of univariate outliers (a) inspection of Z scores
and (b) graphical methods. First I transformed each raw score to its standardized z score, and observed each Z
score against a criterion of 3.29 proposed by Tabachinick (1996) i.e Z score above 3.29 is considered an outlier.
To find out this first Z scores for each of the case across all variables were computed and then frequency tables
were observed for the values greater than 3.29. .The Z value for none of the variable was found so; these three
variables were deleted from further analysis. Second, I inspected the histograms, box plots and normal
probability plots for the purpose of detecting univariate outliers. Since histograms of variables are readily
understood and may reveal one or more univariate outliers. In histograms outlier is a case that seems to be
unattached to the rest of distribution. Inspection of histograms for all remaining variables revealed no detracted
or unattached case (see appendix A).
SCALE ITEMS MSA
PAP
PAP1 .699
PAP2 .693
PAP3 .655
PAP4 .745
PAP5 .755
PAP6 .622
PAP7 .887
Turnover
TO1 .786
TO2 .810
TO3 .777
TO4 .745
TO5 .751
ORG. COMMITMENT
OC1 .804
OC2 .811
OC3 .803
OC4 .814
OC5 .838
OC6 .822
Fourth, I inspected the Communality, h2
, which is the squared multiple correlation for the variable as dependent
using the factors as predictors. The communality measures the percent of variance in a given variable explained by
all the factors jointly and may be interpreted as the reliability of the indicator. When an indicator variable has a low
communality, the factor model is not working well for that indicator and possibly it should be removed from
the model. Low communalities across the set of variables indicate the variables are little related to each other
(http://www2.chass.ncsu.edu). This inspection of communalities did not reveal any communality (for any scale items)
below the threshold of 0.50 (See appendix B).
SCALE ITEMS Loading Cronbach Alpha
PAP
PAP1 .602 <.05
PAP2 .629
<.05
PAP3 .758
<.05
PAP4 .592
<.05
PAP5 .737
<.05
PAP6 .754
<.05
PAP7 .413
<.05
Turnover TO1 .680
<.05

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TO2 .582
<.05
TO3 .656
<.05
TO4 .599
<.05
TO5 .582
<.05
ORG. COMMITMENT
OC1 .594
<.05
OC2 .684
<.05
OC3 .601
<.05
OC4 .568
<.05
OC5 .620
<.05
OC6 .622
<.05
For evaluating four CFAs (seven structural models) Chi-square, GIF, AGFI, TLI, for each model was
evaluated. For all seven models, overall, data fitted the model well. Meaning, for all CFA models the values of
GIF, AGFI, TLI and CFI were well above the level of 0.80. Also RMSEA values for 5 models (out of seven)
were well below the threshold level of 0.08 (see table and appendix C). In sum, we can conclude that all the
seven items internally possessed the quality of unidimensionality.
SCALE CMIN/DF GFI AGFI TLI CFI
PAP 12.71 .863 .726 .651 .767
TI 4.529 .965 .896 .872 .936
OC 3.522 .959 .904 .894 .937
Reliability and Validity analysis
Reliabilities of the five sub scales were assessed through Cronbach Alpha. The Cronbach Alpha for all the
scales is being presented in the table. As we can see, Cronbach alpha for all the scale are well above the
threshold level of 0.70. So, we can say that the scales being used in this analysis are reliable ones.
Convergent Validity
Convergent validity refers to the degree of agreement in two or more measures of the same construct. According
to Roussel et al. (2002), “a construct shows a good convergent validity, if and only the t tests associated with each
of the regression weights are significant (i.e. >1.96)”. For this data, all items loaded significantly positive on their
specified factor/scale (see table). The null hypothesis tests that the coefficients are equal to zero in the population.
For example, in examining the convergent validity of the indicators measuring Perceived Organizational
Politics, the values of the t tests of the indicators were all significant. All 7 values were significantly different
from zero (p <.05). Hence, the convergent validity of PAP, OC, and TI was established. The statistical
significance of the results of the t tests supported the convergent validity of the indicator variables (Anderson
and Gerbing 1988).
Convergent validity

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Construct AVT
PAP .42
OC .37
JS .36
TI .37
Hypothesis Testing:
Finally I tested the hypothesized relationships by using structural equation modeling technique. The results
of the final hypothesized model can be seen in the figure.
As can be seen in the figure, performance appraisal politics had a significant negative impact upon
organizational commitment (B =-.58, p < .05). Hence, hypothesis 5 was supported.
Discussion and conclusion:
This study examined the effects of performance appraisal politics on organizational
commitment, and turnover intention. Initially the perceptions of appraisal politics was viewed as single general
variable, but after factor analysis of the items used to assess the variables, resulted in two independent factors.i.e
one linked to political motives that benefit employees and other is linked to personal bias and punishment motive.
The study hypotheses received support as far as the personal bias and punishment motives were used for
indicating performance appraisal politics.
Employees’ experience reduced job satisfaction, organizational commitment and enhances intentions to quit, when
they perceived that their performance appraisal is based on political consideration and manipulated for personal
biases. Political manipulation of performance appraisal of employees’ is viewed as unfair and injustice. On the
other hand, when employees, perceived that their performance appraisal is manipulated for the purpose to
promote efficient workers and promote positive work group climate, which did not effect the job satisfaction,
organizational commitment and intentions to quit. Another window for future research is opened whether or not
employees’ view performance manipulation for motivational purposes is legitimate; as such acts represent
managerial discretion carried out to ensure the attainment of certain goals. Another need is to answer the question of
the cost and benefits of actual/accurate ratings versus higher levels of employees’ motivation.